intellectual capital as an indicator of regional development

Transcription

ČLANKI
Branko ILIČ, Sabina BERNJAK, Andrej RUS*
INTELLECTUAL CAPITAL AS AN INDICATOR OF
REGIONAL DEVELOPMENT: THE CASE OF THE
SLOVENIAN REGION OF POMURJE
Abstract. One of the key success factors of every region is
an adequate level of intellectual capital provided by the
human capital of its residents. This article aims to show
that low levels of regional development in Slovenia’s least
developed region of Pomurje corresponds to the low levels
of intellectual capital. The article reviews the literature on
the concept and measurement of intellectual capital and
provides operationalization of intellectual capital suitable for assessing its levels on a regional, subnational level.
The results show that Pomurje has lower level of intellectual capital from the national average. Furthermore,
the analysis of rates of growth of intellectual capital indicate the systematic lagging of Pomurje region behind
Slovenian average. The case study highlights the problem
of brain drain as the key contextual factor that influences the size of intellectual capital and negatively affects the
performance of the region thus pointing to priorities of a
more effective developmental policy.
Keywords: Intellectual capital, brain drain, regional
development, Pomurje
Introduction
In today’s knowledge society, increasing amounts of specific knowledge
are required for a successful adaptation to social and technological change.
With ever more rapid technological progress the usefulness of a given
acquired knowledge becomes more short-lived and needs to be constantly
renewed and replenished. Therefore companies are increasingly aware of
the significance of the adequate competences of their employees’, and the
dependence of their market success on the quality of intellectual capital that
they have at their disposal. As a result, the importance of companies’ intellectual capital has already been considerably increased, as knowledge represents the core of intellectual capital.
* Branko Ilič, PhD., Assistant Professor; Faculty of Social Sciences; Sabina Bernjak, MSc. of Sociology;
Andrej Rus, PhD., Associate Professor, Faculty of Social Sciences, University of Ljubljana.
TEORIJA IN PRAKSA let. 53, 3/2016
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Branko ILIČ, Sabina BERNJAK, Andrej RUS
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Similar emphasis on intellectual capital has been taking place on national
and regional levels. Intellectual capital is becoming an increasingly important factor of growth, development, competitiveness, and economic performance of organisations, regions and countries. The investment in the
strengthening of intellectual capital and its management is emerging as a
key trend in economic development policies. The measurement and the
monitoring of the intellectual capital and intangible assets of a nations,
regions and companies has become as important as the monitoring of their
financial statements or balance sheets.
This article analyses the meaning and the role of intellectual capital for
the performance of Slovenia’s eastern-most region of Pomurje, representing a topical issue in the context of current economic and developmental
challenges of the region. By doing so, this article fills the void in national
studies of intellectual capital at the regional level. The article also considers
the wider context of this problem, and its potential implications and message for the regional developmental policy of Pomurje. The Pomurje region
is considered the country’s least developed region, and also one that most
lacks intellectual capital. Therefore, the article addresses this research problem and looks for possible solutions for Pomurje as a region struggling to
retain and improve its intellectual capital. In this paper we attempt to show
the level of intellectual capital of Pomurje compared to the national level
in Slovenia. Than we examine that rate of change in intellectual capital in a
critical period that includes years before, during, and after the crisis trying
to determine the extent to which the region was lagging behind or catching
up with the national average. And finally we use contextual factors in trying
to determine what are the potential drivers that determine the levels and the
rate of change in intellectual capital of Pomurje region.
Economic and regional development
Economic development is a much broader concept than economic
growth. While economic growth refers to the growth of national wellbeing measured usually through GDP (and GDP per capita) growth rate,
economic development denotes qualitative social changes based on quality of life improvement, structural changes and innovations (Senjur, 2002).
There are four distinct approaches to economic development. Schumpeterian approach sees innovations generated through “creative destruction”
between rival firms and industries as key “engine” of economic development (Schumpeter, 1951). Neoclassical approach, on the other side, focusing on growth otherwise states economic development as a result of investment in physical capital (Solow, 1956). The development of the endogenous
growth theory brought further to the fore the importance of two additional
factors – innovation (Romer, 1986) and education (Lucas, 1988), while institutional approach argues for the significance of institutions for economic
and regional development (Rodríguez-Pose, 2013).
Regional development could be understood as economic development
on a regional level (cf. Cooke and Leydersdorff, 2006) and includes regional
developmental factors such as (Kukar, 1995: 9): the existing regional economic structure, natural, human, infrastructural, financial, institutional and
organisational potential. In addition, Florida (2002) emphasizes creativity
as the key factor of economic and regional development stating that only
mutual cooperation between actors of “technological creativity” and innovation, “economic creativity” (or entrepereneurship) and “cultural creativity” accelerates economic and social prosperity.
Regional development theories can be divided into five groups. First
group is referred to the neoclassical “interregional convergence hypothesis” stating that over time, differences in the price of labour and other factors across regions will diminish and tend toward convergence. Location
theory is focused primarily on developing formal mathematical models of
the optimal location of industry given the costs of transporting raw materials and final products. The third considers external economies when firms
may cluster to take advantage of external economies that result from close
proximity to a large number of other firms, while the fourth is built on
Hotelling’s models of spatial competition. The fifth is central place theory as
a more general theory of the spatial location of firms (Dawkins, 2003).
Alternative theories to the interregional convergence hypothesis mentioned above, embrace export base theory and neoclassical exogenous
growth theory. In contrast with more traditional theories the theories of
regional economic convergence emphasize the factors that lead to differential
levels of regional development. “Divergence” theories include Myrdal’s cumulative causation theory and growth pole theory. Structuralist theories examine
regional economic development as a process of structural adjustment both
within and outside the region (e.g. stage/sector theories, profit/product cycle
theories, industrial restructuring theories, flexible specialization and network
theory, Marxist theory of uneven growth and spatial differentiation). There
are also few theories that account for the role of politics and political institutions in economic development, i.e. growth machine theory and the new
institutional economics (based on theory of transaction costs developed by
Coase, Williamson and North). The last group of theories derived from emerging neoclassical perspectives, refer to “Schumpeterian” endogenous growth
theory, which makes technological change and innovation endogenous to the
model, and Krugman’s “the new economic geography”, e.g. “core-periphery”
model where regional clusters of economic activity emerge due to a combination of centrifugal and centripetal forces (for more details see Dawkins, 2003).
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In this paper we draw on economic divergence theories as providing
a framework for the understanding of the long-term underdevelopment
of Pomurje region. Compared with more developed (central) regions, the
less developed, peripheral regions (e.g. Pomurje) usually exhibit lower
regional GDP per capita, lower average wage level, higher unemployment
rate, worse infrastructure linked with higher transportation costs as well as
financial and qualified human capital outflows to central regions causing
regional inequalities and unequal regional development (Armstrong and
Taylor, 2000). Central regions, in contrast, can achieve either Ricardian comparative advantage or Porter’s competitive advantage over other regions by
benefiting from “constructed” advantage, i.e. knowledge-based construction which requires interfacing developments in the following knowledgeenhancing areas (Cooke and Leydesdorff, 2006: 10–11):
a. Economy – regionalization of economic development, ‘open systems’
inter-firm interactions, integration of knowledge generation and commercialization, smart infrastructures, strong local and global business
networks.
b. Governance – multi-level governance of associational and stakeholder
interests, strong policy-support for innovators, enhanced budgets for
research, vision-led policy leadership, global positioning of local assets.
c. Knowledge Infrastructure – universities, public sector research, mediating agencies, professional consultancy, etc. have to be actively involved
as structural puzzle-solving capacities.
d. Community and culture – cosmopolitanism, sustainability, talented
human capital, creative cultural environments and social tolerance as
well.
All four areas of development enhance knowledge creation and integration in a region and contribute to the regional development by means of
increasing intellectual capital to which we turn in the next section.
Conceptualisation of intellectual capital
Intellectual capital encompasses all processes and assets that are usually
not shown in the balance sheet (Roos et al., 2000: 17). Knowledge represents the core of intellectual capital. Intellectual capital can be defined as
“the end result in the process of knowledge transformation or as the knowledge that is transformed into intellectual property” (Starovic and Marr, 2003:
6). David H. Luthy (1998: 3) claims that even several decades ago intellectual
capital had been becoming the “preeminent resource for the creation of economic wealth”. By investing in intellectual capital companies are believed to
achieve a higher degree of value added, a better reputation, a competitive
advantage and faster economic growth and development (Lazuka, 2012:
9–10). In the first, positive definitions, an organisation’s intellectual capital
was defined as the set of knowledge of all the employees in an organisation
and the set of practical use of this knowledge in the form of guaranteed
quality symbols, trademarks and processes (Roos et al. in Mihalič, 2009: 15).
According to the negative definition, intellectual capital represented everything intangible that could produce value in the company (Mihalič, 2009:
15). Today, numerous authors (Bontis, 2000; Bontis, 2002; Sveiby, 2001 etc.)
define intellectual capital mainly as the organisation’s intangible and hidden
value that creates added value.
In other words, intellectual capital is the sum of all the knowledge within
the company that is used for competitive advantage (Nahapiest and Ghoshal in Huang and Wu, 2010: 584). It can be assumed that a company’s competitive advantage depends on the efficiency of its building, distribution,
upgrading and use of knowledge (Huang and Wu, 2010: 584). Intellectual
capital can exist in tangible or intangible forms. In tangible form it can be
identified as patents, trademarks, plans, licences, programmes etc. and represents a company’s tacit knowledge. The intangible form of intellectual
capital exists in the employees’ minds in the form of knowledge, capabilities, problem solving, and experiences etc. as an explicit form of knowledge. One of an organisation’s aims is that tacit knowledge transforms into
explicit knowledge, becomes the organisation’s property and is inalienable
(Jelčić, 2004: 22).
Components of intellectual capital
Rather than being a homogeneous resource intellectual capital consists
of a sum of all intangible assets including knowledge or human capital,
structural capital, relational capital and social capital (Bontis, 1999). Following Bourdieu’s differentiation between different forms of capital all these
forms represent structural elements of intellectual capital (Bourdieu, 1986).
Human capital
In the 1960s the concept of human capital was analytically elaborated
by the economists Schultz (1961), Mincer (1958) and Becker (1964) who
developed the so called human capital theory that stems from the idea
that employees’ knowledge and experience can be considered capital.
The increased quantity and quality of human capital acquired through
the years of education or training increase the marginal labour productivity and the quality of job performance in the company which in turn
increases wage level (Becker in Dimov and Shepherd, 2005). In business
terminology human capital is defined as the combination of basic factors,
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namely individual quality, individual competence and individual motivation (Fitzenz, 2000: 18). Human capital is the intangible resource hiding in
the existing individual knowledge and competence, with the extent of its
usage depending on the form of management and treatment of people at
work in a given company (Edvinsson and Sullivan, 1996: 363; Bec, 2014). All
knowledge, experience, personal characteristics, competence, motivation,
creativity and adaptability possessed by individuals should be appropriately
treated, managed and controlled for these factors of the human capital to be
used in practice in the most efficient and effective way to contribute to the
creation of a new value added of the company (Mihalič, 2006: 44).
A common feature of different definitions of human capital is that it
deals with the quality of labour force as the capital which when invested
yields higher returns, both for the individual through higher wages and for
the company through increased productivity. Human capital that contains
employee knowledge, their skills, abilities, capacities and competences represents an important component of intellectual capital.
Structural capital
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Structural capital includes all data bases, organigrams, manuals and intellectual property, along with everything that a company considers higher
value than its tangible value. Structural capital is part of intellectual capital
that has been created in the organisation by human capital and has become
the property of the company; it is what “remains in the company when
employees go home at night” (Roos et al., 2000: 30; Bec, 2014). Structural
capital offers direct and indirect support to human capital: direct in the
form of tangible elements such as office inventory, and intangible elements
such as information systems, computer programmes, work procedures,
marketing designs and business know-how. Indirect support to human
capital includes tangible elements such as buildings, electricity, plumbing,
and intangible elements, such as strategic plans, payment systems and cost
structure (Sullivan, 2000: 232). Structural capital enables human capital
to increase its value added. It is what was created by human capital but is
owned by the company (Pučko, 1998: 559).
Social and relational capital
The third component of intellectual capital is social capital occasionally
referred to in economic literature as relational capital. Social capital is represented by the relations between members of the family (Coleman, 1988),
local communities (Wellman, 1979), urban centres (Portes, 1993), organisations (Burt, 1992) and societies (Putnam, 2000). On one hand social ties
between people serve as levers to access resources owned by people that
are related to us (Burt, 1990), which increases the range of resources available to the individual. The complexity of social capital stems from the fact
that it only enables access, but not property of resources, which is why the
access to our contacts’ resources is conditioned by the people to whom we
are related. Therefore, while social capital enables access to a wider range
of resources, the mobilisation of these resources depends on the strength
of the ties and structure of the social network (Burt, 1990; Rus, 1999). Social
ties also serve as prisms: our social status in society is largely determined by
who is part of our social network (Podolny, 2001). This means that social
capital includes direct and indirect components enabling on one hand
a direct access to resources, while on the other through our social status
opening opportunities for access to resources that exist beyond the limits
of our social network. Often, this approach is used in very diverse problems
such as the analysis of social support networks (Šadl and Hlebec, 2007), the
development of entrepreneurship (Rus and Iglič, 2005) or whole societies
(Iglič, 2014).
Bontis considers social capital in organisations as relational capital and
defines it as a set of organisational relations consisting of the social network
of co-workers, their satisfaction and their loyalty to the company (1996:
42). According to Wiig, organisational relations also include relationships
between an organisation and its stakeholders (1997: 401). The firmer, more
open and trustworthy these relations are the larger the relational and in turn
intellectual capital is. While relational capital stresses the meaning of direct
contacts, social capital also includes the value of direct relations. The larger
the ramification of a company’s contacts with other economic subjects, the
larger its social and in turn intellectual capital. In terms of content, relational
capital refers to those relationships with buyers, clients, suppliers, emplo
yees, customers and business partners that create a new value. These are
the relations between the company’s internal and external stakeholders that
contribute to the creation of its value added (Mihalič, 2009: 40) and are the
source of its competitive advantage (Kešeljevič, 2003).
Management and measurement of intellectual capital
The purpose of managing intellectual capital is its building, development, retention and strengthening (Mihalič, 2009: 28). The management of
the intellectual capital of a region mainly depends on its management in
regional companies and on the coherent operation of national and regional
institutions for the promotion of investment in innovation (such as regional
developmental agencies).
Management of intellectual capital means that intellectual capital
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becomes the focus of all the activities of a company directed toward the
future growth and strengthening of its capabilities and simultaneous minimization of its weaknesses. The management of intellectual capital represents the transformation of knowledge into what embodies a direct value
to an organisation (Brennan, 2001: 425) or a region. The implementation
of intellectual capital management policy is based on the belief that a company’s intangible value as such does not create value or generate growth,
but can be developed and bring success only in a certain context or through
optimum management (Lev and Daum, 2004). In our opinion the management of intellectual capital is the strongest component of operation that creates value added and increases the wealth of organisations, regions or countries. Aiming to satisfy and motivate its employees, efficient management of
intellectual capital contributes to the improvement of business processes,
the possibilities of creating new value, product development, better use of
resources and better corporate design (Branković–Merdžo et al., 2015: 362).
According to Skyrme (2007) only “what gets measured, gets managed”. It
is by measuring their intellectual capital and publishing the data that innovative companies distinguish themselves from non-innovative ones. Intellectual capital can be measured. There are numerous methods of measuring
intellectual capital that can be classified into four main approaches under
the name of ABBA – Asset, Benefits, Baseline and Action (Skyrme, 2007).
Sveiby’s division (Sveiby, 2010), which represents an extension of Luthy’s
(1998) classification, speaks about four basic approaches for measuring
intellectual capital, namely Direct Intellectual Capital methods (DIC), Market Capitalization Methods (MCM), Return on Assets methods (ROA), and
Scorecard Methods (SC).1 Each approach has many variations and refinements.
The selection of the method depends on numerous factors such as the
organisation’s activity, its development of human resources, and financial
position etc. Sveiby (2001) states that no method suits all purposes, which is
why the method for measuring intangibles should be selected according to
the purpose and situation of measurement and the target audience.
Undoubtedly, the measurement of intangible assets brings certain advantages and benefits to the company, region or country. Many authors think
that a company’s balance sheets of assets and liabilities do not show the correct state of its assets or its real value (see for example Van Deventer, 2002).
The company that makes profit has “something more” that needs to be recognised, measured, and thereby managed, upgraded and also rewarded
(Peršak, 2011: 2). With knowledge becoming the most important economic
resource in the contemporary conditions of the economy, intellectual
1
For a more detailed description of these methods see Sveiby (2010).
capital is the economic version of knowledge. To obtain the results that lead
to companies’ competitive advantage it is therefore necessary to manage
and measure both financial and intellectual capital (Bec, 2014).
Regional Intellectual capital
The intellectual capital of a region is defined as the region’s ability to
create value ensuring the long-term competitiveness of its economy, and
to determine the potential for its future growth (Antoljak, 2014). The intellectual capital of a region consists of five components, namely human capital, market capital, organisational-process capital, renewal-and-development
capital and financial capital (Lin Yeh-Yun and Edvinsson, 2010: 4).
Human capital is defined as individuals’ ability to engage in and carry
out activities that are important for regional economic and social development. It represents the intellectual wealth of all the individuals from a certain region (Bontis, 2004: 20). OECD (in Lin Yeh-Yun and Edvinsson, 2010:
254) defines human capital as consisting of the knowledge of facts, laws
and principles, knowledge referring to team work, and other specialised
and communication abilities. Education is the basis of human capital. Thus,
human capital is reflected in the qualified workforce, the degree of education of the employees, the degree of literacy, the degree of enrolment to
higher education, and public expenditure for education etc. (ibid: 254).
The human capital of a region is not determined by the educational
attainment of its residents but by the extent it is able to retain and develop
this human potential and employ it toward economic growth. Human capital of a region is therefore positively affected by education but and negatively affected by the outflow of educated individuals from the region to
more developed areas or even other countries. In cognitive theory brain
drain belongs under the broader notion of migration. When speaking of
migration, we have in mind the movement of people or groups of people
from one territory to another, which often leads to a permanent change of
place of living (Bevc et al., 2004: 3). One of the most well-known definitions
of brain drain was given by Walter Adams (1968: 1), who understands brain
drain as the loss of vital resources without replenishment of this loss, which
means that human capital leaves the areas, in which it could have had a positive effect on prosperity, for new environments that already have enough
trained staff. Docquier and Marfouk (2004) define brain drain as a proportion of the total number of working-age individuals older than 25 years with
an educational level not lower than post-secondary education who grew up
in one country and now live and work in another.
Market capital is another type of capital that represents the abilities and
achievements of a region in providing attractive and competitive solutions
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to satisfy the needs of its international clients, and at the same time its
capability of exchanging knowledge with the rest of the world (Bontis in
Lin Yeh-Yun and Edvinsson, 2010: 254). This is the capital that is needed
to maintain good and authentic international relations (Bontis, 2004: 23).
This includes cross border investment and achievements in external international relations, export of goods and services, openness to other cultures,
and degree of globalisation etc. (Lin Yeh-Yun and Edvinsson, 2010: 254).
Organisational-process capital is defined as the knowledge stock embedded in the infrastructure of a region. These are ICT systems that enable the
easier creation of, access to, and dissemination of information (hardware,
software, data bases, organisational structures) that support human capital
(Bontis, 2004: 21).
Renewal and development capital provides a kind of basis for the continued operation of companies in the region and a support instrument for
their start or restart (Južnik, 2004: 60). Renewal and development capital
represents the future intellectual wealth of the region and its capability for
innovation that maintains its competitive advantage and continual economic growth (Bontis, 2004: 24).2
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The Pomurje Region
The Pomurje region lies in the South-East of Slovenia and extends over
1,337 km2 or 6.6 % of the total surface of the country. It is bordered by Hungary, Austria and Croatia, which provides the region with an attractive geostrategic position. In terms of size it is Slovenia’s seventh statistical region.
The central town of the region is Murska Sobota. The population of Pomurje
amounts to around 120,000 inhabitants which represents 5.8 % of Slovenia’s
total population. There are 27 municipalities in the region (SURS, 2014: 40;
RRA Mura, 2015: 16–17).
The Pomurje region belongs to the least developed Slovenian regions.
Compared to other Slovenian regions its economic activity is mainly oriented to activities with low added value per employee. The Pomurje economy is characterised by intensive farming, whose development is made
possible by the extensive plains3, fertile soils and a favourable continental
climate. The region is considered to be very touristically attractive with 10 %
of overnight stays annually of all tourists that visit Slovenia (SURS, 2014: 40).
However, its remote position adversely affects the region’s economic
position and the living conditions of its residents. Among other things, this
2 Along with all other capitals, another component of regional intellectual capital that needs to be
considered is financial capital that is normally expressed in per capita GDP.
3 It is the flattest and most agrarian (80 % of all farmland in use) statistical region of Slovenia (RRA
Mura).
is reflected in the low GDP per capita (in 2012 amounting to EUR 11,872)
and the lowest disposable income per capita (in 2011 EUR 9,008 per capita):
Pomurje is also the region with the highest registered unemployment rate
reaching over 20 % at the beginning of 2014. For several years the region
records negative natural population change, which is the largest in the
country (RRA Mura, 2015: 17).
Another problem in the region is a poor educational structure of its population that notably falls behind the rest of Slovenia. Pomurje has the lowest
percentage of the population with a completed tertiary or post-secondary
education, but nonetheless, it consists of the smallest share of unemployed
with completed higher education (Toplak Perović, 2012). Most unemployed
have a first and second degree of education. Having only some constituent
schools of a few post-secondary schools, the Pomurje region has no higher
education institution. Thus, young people leave to study in other regions,
which for Pomurje represents human capital outflow, with young graduates not returning to the region after they complete their studies (RRA Mura,
2015: 18). All these reasons function as “push” factors for young people to
leave for other places, regions, and countries.
Another indicator of brain drain in the region can be obtained from
Pomurje Academic and Scientific Union (PAZU), an association that brings
together those former or present residents of Pomurje who hold doctorate
in science or philosophy. The association which has currently 146 members,
estimates, that over half of them have emigrated from the region and now
live and work in other parts of Slovenia or abroad. Further evidence points
out that out of 450 doctors of sciences from Pomurje, the majority of them
now live and work outside of the region (Žunec, 2015).
To deteremine the reasons for brain drain from the Pomurje region, we
conducted a survey among the members of PAZU and other highly educated Prekmurians who have emigrated from the region. We wanted to
learn why they emigrated from the Pomurje region? The survey questionnaire provided the respondents with six reasons for emigration, namely:
work, family, education, religious reasons, political reasons, and other. The
answer that was picked most often was work (42 %), followed by education
(37 %), while only a minority emigrated due to family reasons (16 %). Since
work was most often the cause of brain drain we were interested in whether
they thought it was difficult to get employment in Pomurje. The vast majority of respondents (63 %) responded with “yes”, with 29 % chose the answer
“I do not know”, since they had never looked for work in Pomurje or they
emigrated during their study. Only 8 % thought that employment was not an
issue.
The findings show that work and employment related issues are indeed
the main reasons for emigration from the region. They also give substance
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to the data from PAZU regarding large majority of émigrés from the region
among their members. They also point to the vicious spiral of underdevelopment. On the one hand the underdevelopment of Pomurje is the main
cause of brain drain from the region which, on the other hand, reduces
intellectual capital of the region and inhibits its economic development.
Methods
Intellectual capital index of a region
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The IC index calculation belongs to the group of scorecard methods.
Scorecards methods show the non-monetary value of intangible assets
through determining their individual components. Four individual components of intellectual capital indicators are determined that monitor the performance of intellectual capital, and are shown in graphs or on scorecards.
These indicators are then added up and their sum represents the value of
intellectual capital (Sveiby, 2001).
IC index calculation is based on the definition of the human development index (HDI) as the indicator that shows well-being at three levels of
social development:
a. health (life expectancy at birth for the monitoring of lifespan and health
conditions),
b. income or access to resources that allow people a decent living standard
(GDP per capita according to purchasing power),
c. level of education and knowledge: gross inclusion and literacy rate that
shows the combined enrolment ratio at different levels of education or
adult literacy rate (ARSO, 2010; comp. UNDP, 2014: 33; UMAR, 2013: 174–
175; UMAR, 2014: 62).
Since human capital is the constituent part of intellectual capital, and is
also encompassed in HDI, then HDI can be understood as a partial correlate of the IC index in the macro model of indicators of sustainable social
development (Makarov, 2010). The IC index can be calculated at different
levels such as for profit and non-profit organisations, regions or countries
(Maček and Možina and Kovač, 2006: 100; Bontis, 2004). The idea is the same
for all three levels, with only individual level indicators requiring somewhat
different approach. Literature includes attempts to define the IC index for a
region. For example, Nick Bontis (2004) calculated the IC index for Arabian
regions. His model was taken here as the basis for the calculation of the
intellectual capital index of the Pomurje region. The experimental model of
measuring regional intellectual capital has also been used in Slovenia, following the Bontis’ methodology (Južnik, 2004). Similar model was also used
by Carol Yeh-Yun Lin and Leif Edvinsson (2010) to calculate the intellectual
capital of the Nordic states.
Operationalisation of the four components of the IC index
The regional IC index consists of four components, namely human
capital, market capital, renewal and development capital, and organisational and process capital (Bontis, 2004: 17). Indicators are defined for each
component of regional intellectual capital to contribute to the discovery,
understanding and monitoring of the invisible resources of the region. The
selection of indicators was made on the basis of the IC index calculations by
several authors (Bontis, 2004; Južnik, 2004; Mihalič, 2009; Lin Yeh-Yun and
Edvinsson, 2010). However the list of indicators is somewhat different than
in the prior work due to availability issues in Slovenia, conceptual clarifications of some of those indicators for Slovenia and due to inclusion of some
other relevant indicators.
We selected 26 indicators that we consider to have the most influence
on intellectual capital of a region (see Appendix 1). The 26 indicators were
grouped in 4 groups to represent four different components of intellectual
capital. Together they constitute the aggregate indicator, i.e. the IC index.
The following indicators grouped in four components were:
• market capital is measured as 1) trade balance in USD (the ratio of
export over import), 2) the number of companies with the acquired ISO
certification (ISO 9001 of quality management system standard and ISO
14001 environmental management system standard), 3) the number of
tourists, 4) the number of emigrants (emigrant Slovenian citizens) and 5)
the number of immigrants (immigrant foreign citizens).
• Human capital was operationalised with the following indicators: 6) number of students of post-secondary professional schools, 7) number of students of professional colleges, 8) number of students enrolled at Master
or specialization level, 9) number of higher education institutions (public
and private), 10) the number of graduates of higher education undergraduate programmes, 11) the number of those with higher education among
all employees, 12) the number of libraries (full members of the COBISS
system) and 13) the number of the active working population.
• Organisational-process capital was measured with indicators: 14) the number of providers of continuing education (people’s universities, public
and private providers of further education, driving schools), 15) the number of participants of continuing education, 16) the number of (adult) participants in the programmes to acquire education (programmes to acquire
lower and secondary vocational, secondary technical, professional and
general education for youth and adults), 17) the number of cinemas, 18)
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museums, galleries, and exhibition grounds, 19) the number of cultural
centres, as well as 20) the number of radio and TV subscribers.
• Renewal and development capital is represented in the study by 21) gross
domestic expenditure for R&D activities, 22) the number of researchers,
23) the number of research organisations, 24) the number of subjects
of innovative environment, the 25) number of newly established enterprises, and 26) the number of fast-growing enterprises.
It needs to be pointed out that one indicator, namely the number of persons who emigrated from Slovenia and Pomurje have a negative impact on
the IC index, which is why this indicators was given a negative value and
consequently its value was deducted in the calculation of IC index. Due
to the complexity of data acquisition some of the data was determined by
means of estimation.
Data collection
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We used publicly available databases to extract indicators of intellectual
capital described above. Two most important sources of the data were the
Statistical Office of the Republic of Slovenia and the Employment Service
of Slovenia. We complemented those with some other institutional sources,
to establish the economic position of the region, and the ensuing state of
its intellectual capital. The data were collected for eight years for the period
from 2006 to 2013. The period is interesting because it includes both the
period of unprecedented growth and the years of economic crisis. We gathered the data for Slovenia and for the Pomurje region in order to compare
the intellectual capital of the country with the one of the region across eight
years of observation. We managed to gather the data for 26 indicators defined
above whose values were obtained directly from the available statistical data
or were derived from the analysis of other institutional sources. For example, some of the data for the Pomurje region was not readily available as the
Statistical Office does not report all of the data broken down by region. Thus
we contacted the Pomurje municipalities that forwarded us information on
the number of museums, exhibition grounds, houses of culture, cinemas.
We obtained the data on the number of Radio and TV subscribers from the
national broadcaster RTV Slovenia. The number of libraries in the region was
obtained from national agency IZUM4 while the number of entities of innovative environment were obtained from the national agency SPIRIT5.
4
Institute of Information Science.
Public Agency for Promotion of Entrepreneurship, Internationalisation, Foreign Investments and
Technology formerly known as JAPTI
5
Calculation of weights
The weighting of different indicators can significantly affect the value
of IC. For example, one could argue that the number of museums and the
number of researchers are two very different indicators that should be
weighted according to their significance. The weighting of different indicators could be derived from theoretical considerations or by means of subjective evaluations of relevant actors in the region. We decided on subjective
evaluations. Subjective weights by key actors of development should reflect
real differences in the significance of each indicator as perceived by key
practitioners in the region. could be done by the companies in the Pomurje
region as they are the key actors of its economic development. On-line survey questionnaire was sent to the electronic addresses of 90 companies
in Pomurje addressed mainly to their human resources offices or general
managers. The list was obtained from the regional development agency that
maintains a register of 90 biggest companies in the region. The companies
in the register were drawn from widely diverse sectors. The most numerous were professional services organisations, followed by the construction
industry, the metal processing industry6, food and agriculture, and ICT. 31 %
of companies had over 100 employees. 38 % of companies were in existence for a period of 20 to 50 years. As many as 9 % of companies were 100 %
foreign-owned. 74 % of companies mainly served the domestic market.
We received 58 questionnaires with valid responses resulting in 64%
response rate. The first part of the questionnaire included some general
questions (the organisation’s activity, number of employees, market share)
while the second part dealt directly with intellectual capital. For each of the
26 indicators of IC we asked the respondents to indicate their perceived
significance of an indicator on the three-point scale of low, medium or high.
We used these responses to calculate the weights for each indicator of IC.
Calculation of the Index of Intellectual Capital and Relative Index of
Intellectual Capital
We calculated two measures of IC. In order to compare the levels of IC
between Slovenia and Pomurje, we normalized the indicators and added
them up within each year. The value of an Index of Intellectual Capital IIC has
no intrinsic meaning but the normalization allows for comparison between
Slovenia and Pomurje region. We made this calculation with unweighted
and weighted data. In order to determine the dynamics of change of the
IIC over years we calculated relative IIC where previous year served as a
6
The strongest industry in the region in terms of revenue (PGZ 2014, 17).
593
baseline for the current year IIC. The relative IIC was calculated for Slovenia
and Pomurje region for all the years and allowed the comparison between
the two in terms of the growth rates of IIC between the two. The method of
calculation of intellectual capital is modelled on Bontis (2004). The method
of calculation of annual rates of growth of the IIC follows closely the experimental model presented by Južnik (2004). Again we used both weighted
and unweighted data.
For the calculation of Intellectual Capital Index for Slovenia and Pomurje
region we had to normalize the data. The raw data were first normalized by
dividing the data with population size of Slovenia and Pomurje respectively
in order to account for the size of unit under observation. We thus obtained
per capita measure of each indicator. Since the indicators were not comparable in terms of their scale, we normalized them by dividing each indicator
with the mean value of an indicator in a given year. Indicators were thus
brought to a common scale and were summed up by category within each
year. Intellectual capital index is a sum of all indicators within a year.
Index of Intellectual Capital IIC is therefore calculated as:
594
here Int is a normalized indicator n for a year t and IICt is an Index of
Intellectual Capital for a given year t.
Index of Relative Intellectual Capital RIIC is similarly calculated as:
were Int is a normalized indicator n for a year t, In(t-1) is a normalized
indicator n for a prior year (t-1), their ratio expresses the rate of growth in
the indicator n and RIICt is a Relative Index of Intellectual Capital for a given
year t.
Calculation of weighted indices and weighted relative indices follows
the same logics with the normalized data multiplied by normalized weights
and emulates (Južnik, 2004: 62). However, the weighted results are almost
identical to the unweighted ones and are not reported.
Results
Table 1 shows clearly indicate the extent to which Pomurje region lags
behind Slovenian average. It is consistent with the concept of intellectual
capital to find the IIC over time relatively stable, as intellectual capital reflects
both infrastructural investments and human capital that do not change
abruptly. The data in the table 1 also reveal the structure of differences
between the national and regional IC. The differences in market component
and organizational (i.e. “infrastructural”) component of IC are small relative
to the other two components. The largest differences between the national
and regional IIC arise in the human capital component and development
and renewal component supporting the hypothesis that the intellectual
capital is most critically affected by people in their intellectual potential and
their creative and developmental capacity. Interestingly, we note that organizational component exhibits only minor differences indicating that infrastructure per se is not the determining factor in the formation of intellectual
capital. This suggests that additional investment in infrastructure might not
yield developmental benefits without the enhancement of the human capital (such as prevention of brain drain).
Table 1: INDEX OF INTELLECTUAL CAPITAL BY COMPONENT AND YEAR
2006 2007 2008 2009
2010
2011
2012
2013
Market
capital
Slovenia
3,70
3,74
3,49
3,63
3,41
3,29
3,76
3,68
Pomurje
2,19
2,08
2,22
2,23
2,39
2,46
2,06
2,22
Human
capital
Slovenia
10,02
9,94
9,92
9,85
9,81
9,67
9,73
9,78
Pomurje
5,98
6,06
6,08
6,15
6,19
6,33
6,27
6,22
Slovenia
6,89
6,69
6,62
6,41
6,46
6,40
6,49
6,46
Pomurje
7,11
7,31
7,38
7,59
7,54
7,60
7,51
7,54
Slovenia
8,05
8,09
8,03
8,17
8,15
8,40
8,28
8,34
Pomurje
3,95
3,91
3,97
3,83
3,85
3,60
3,72
3,66
Slovenia
28,67 28,46 28,06 28,06 27,83 27,76 28,26 28,26
Pomurje
19,22 19,35 19,66 19,80 19,96 19,99 19,56 19,64
Organizational
capital
Renewal
and development
IIC (total)
Source: Ilič, Bernjak, Rus (2016).
Table 2 provides the comparison between the rates of growth in IIC in
Slovenia and Pomurje region. The results reveal that there is a trend of deterioration of intellectual capital from year to year at the national as well as
regional level indicated by any number that is lower than 100. This finding
is surprising in that the decline is noted also for the two years preceding the
recession. The decline in IIC was therefore enhanced rather than caused by
at the height of recession in 2010 but the negative year-on-year trend was
present in every year of observation.
The second result gleamed from the Table 2 are differences in RIIC
between Slovenia and Pomurje. In all but one year the RIIC is smaller in
Pomurje region than in Slovenia indicating that the deterioration of IIC in
595
Pomurje was faster than in Slovenia as a whole. This result points to the
lagging of Pomurje region behind Slovenia. Not only that the level of IIC
in Pomurje is much lower than the national average. There seems to be
also a stronger negative trend toward deterioration of intellectual capital
in Pomurje compared with Slovenia. Taken together the results indicate
that Pomurje is on the path of a vicious circle. Lower intellectual capital in
the region is accelerating its depletion of intellectual capital thus increasingly inhibiting developmental potential of the region. This finding resonates with Myrdal’s theory of “cumulative causality” implying on the one
hand positive developmental spirals of already successful regions and, on
the other hand, mutually reinforcing negative trends leading to divergent
regional development with Pomurje increasingly lagging behind Slovenian
average (cf. Dawkins, 2003).
Table 2: RELATIVE INDEX OF INTELLECTUAL CAPITAL BY COMPONENT AND
YEAR
596
07/06
08/07
09/08
10/09
11/10
12/11
13/12
Market
capital
Slovenia
66,05
53,10
62,28
48,34
54,22
48,14
65,40
Pomurje
62,13
61,27
57,64
55,84
59,02
12,82
68,77
Human
capital
Slovenia
103,86 105,65 107,68 100,18 103,08 103,19 100,75
Pomurje
91,96
92,05
93,71
87,21
93,77
Organizational capital
Renewal
and development
Slovenia
98,27
106,01
95,70
98,84
100,50 103,14 103,20
Pomurje
106,11 107,12 100,11
98,39
102,88 100,16 103,61
Slovenia
108,85 111,91 104,27
98,91
109,81 104,33 104,35
Pomurje
108,24 119,57
99,58
95,05
100,78 118,03 102,93
Slovenia
94,26
94,17
92,48
86,57
91,90
89,70
93,43
Pomurje
92,11
95,00
87,76
84,12
89,11
79,75
90,26
RIIC (total)
88,00
85,74
Proposals for regional developmental policy and for the
improvement of the situation in the region
Regional developmental policy and the direction of the development of
the Pomurje region should follow a faster restructuring and keep pace with
the most developed Slovenian regions. Considering our analysis, it implies
that the development of the region should move in the direction of the
improvement of the economic situation and the reduction of brain drain.
To take the opportunities that are offered, better drawdown and utilization
of European funds can help. The residents of the region should be given
the opportunity for a quality life, the possibility to develop their own potential and sustainable living within the environment. In achieving this aim the
region will face numerous, mainly, environmental challenges in the future.
In the field of demographic development it will be necessary to stop the
trend of depopulation and brain drain, increase the employment rate, and
improve the educational framework of the region. These issues could be
improved by founding new enterprises and a professional school to enable
the acquisition of specific knowledge, particularly for professional profiles
lacking in the region (engineering and metal processing, medicine, construction, the hospitality industry) in order to reduce the number of young
people that leave the region for their education. Considering the geographic
position of the region, it could have a certified school that would also be
attended by students from other countries.
It is necessary to connect education with the regional economy. Young
people from Pomurje are basically forced to leave the region, due to a lack
of an educational-entrepreneurial “gravitation centre”. Instead, they are
gaining experience through study and looking for employment opportunities in other Slovenian or even border Austrian regions. Attention should
be given to occupations with a shortage and retaining young people in the
region with scholarships. While on the other hand, while naturally, educated
personnel should be ensured adequate job positions, with only a few large
companies in the region this presents a problem. Although there is a substantial number of small, medium and micro enterprises in the region, they
only offer limited degree of employment.
One of the possibilities to increase employment is to encourage entrepreneurship. The successful Pomurje companies could create an entrepreneurial and research centre where young people could gain experience and
practical knowledge. Jobs with high value added would need to be created,
which would also raise the economic power of the region, as Pomurje has
the status of the region with the cheapest workforce with no value added.
Additionally, a closer interconnection between entrepreneurs is needed,
particularly in the intergenerational exchange of knowledge and ideas.
In tourism, high value-added offers need to be developed for wealthy
guests who are willing to pay more for unique services, while the residents
of the region should be encouraged to learn foreign languages for tourism.
The central town of Murska Sobota, that presently does not offer much for
young people, should be revived as the centre of the region. An improved
access to ICT should be provided for marginal communities.
Industrial policy would need a restructuring of traditional industry to a
modern, technologically advanced one, that would be interesting for foreign
597
598
countries; further, it would need to increase the exports to developed foreign markets7, strengthen R&D investment, and most of all increase the
degree of self-sufficiency in locally grown food and reduce food imports,
as the region has favourable conditions for farming. With possessing sufficient renewable resources, mainly water, wood and geothermal energy, the
region can also become self-sufficient in energy. International inclusion in
inter-regional co-operation should be strengthened as well.
All these measures would contribute to the increase of intellectual capital, prevention of brain drain and, in turn, the performance of the region.
While in statistical terms, Pomurje region always stands out as the weakest
region in Slovenia, there are several bright points that are already strengthening intellectual capital in Pomurje. There are several successful companies with strong export orientation (Radenska d. d., Arcont d.d., Chartago
d. d. and others). Additionally, many people from Pomurje8 hold important
positions in business and public sphere both in Slovenia and abroad. There
is also a strong awareness of the highly educated who have left the region,
that their departure has had harmful consequences for regional development. Pomurje Academic and Scientific Union (PAZU) is one such organization that is reaching out. Its purpose is to establish a creative academic
environment promoting interconnections between its members who, even
if they do not live in the Pomurje region, could occasionally contribute with
their work and knowledge to the development of their home region. PAZU
is the promoter of developmental ideas and at the same time the “driving
force” that strives to ensure that these ideas be realised.9
Conclusion
In contemporary times, intellectual capital increasingly influences
the creation of the added value of companies, regions and countries. Its
increased significance requires monitoring, measurement and management, either at the level of a company, a region or a country. The study of
the components and factors of intellectual capital is rather complex and, at
the level of regions, is an insufficiently researched subject that represents a
challenge for the creators of economic and regional developmental policy.
7
Furthermore the region has a favourable geographical position covering an approximate 12-million market within the diameter of 300 km. The border territory, distanced about 200 km from four capitals (Viena, Budapest, Bratislava and Zagreb), provides opportunities for a strengthened cross-border integration and co-operation in different fields (RRA Mura, 2015: 63).
8 Born in the Pomurje region, but emigrated.
9 A member of PAZU can be any doctor of sciences or top artist that is born, lives or has lived in
Pomurje or expresses through their production their belonging to the people and landscape of Pomurje
(PAZU).
The Pomurje region could become more developed if it succeeded in
retaining the highly educated workforce that would (in turn) promote faster
development in the region. More investment in research and development
is needed, particularly in so called eco-innovation, along with taking the
numerous opportunities offered in the sectors of tourism and agriculture
that are seen as potentially the most promising fields for the economic performance of the region.
Furthermore, it is also important to retain the knowledge of highly educated and capable young individuals that are already strongly influencing
the development of the region. Young people should perceive life in the
region as attractive, or they will leave the region, which will further deepen
the problem of a lack of regional intellectual capital. With the ageing population, the depopulation of capable individuals will lead the region towards
economic stagnation and degradation. Since Prekmurians are leaving for
other countries and regions mainly for better work opportunities, a more
attractive taxation policy, better housing conditions and more advanced
technology should be provided to offer them adequate jobs, satisfactory
wages, creative opportunities, and the possibilities of personal development within their region. Young people from the region should be enabled
to participate proactively in the formation and implementation of the developmental policy of the region through public tender awards for proposals
for improvement, while at the same time bridging the generation gap to
connect the young, as the source of ideas and optimism, with the old as
the source of experience. Given the importance of intellectual capital for
regional development and the detrimental effects caused by brain drain, it
should be recognized that investments should not be directed to infrastructural projects but primarily to the measures that would lead to the retention
of human capital and renewal and developmental capital.
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Appendix 1: THE LIST OF INDICATORS OF INTELLECTUAL CAPITAL
Market capital
Human capital
• number of students of post-
secondary professional schools
• number of students of professional
• trade balance in USD
• the number of companies with the
• the number of tourists
• the number of emigrants
• the number of immigrants
• the number of graduates of
acquired ISO certification
Organisational-process capital
604
colleges
• number of students enrolled at
• the number of providers of
continuing education
• the number of participants of
continuing education
• the number of (adult) participants
in the programmes to acquire
education
• the number of cinemas
• museums, galleries, and exhibition
grounds
• the number of cultural centres
• the number of radio and TV
subscribers.
Master or specialization level
• number of higher education
institutions
higher education undergraduate
programmes
• the number of those with higher
education among all employees
• the number of libraries
• the number of the active working
population.
Renewal and development capital
• gross domestic expenditure for R&D
activities
• the number of researchers
• the number of research organisations
• the number of subjects of innovative
environment
• the number of newly established
enterprises
• the number of fast-growing
enterprises.

intellectual capital as an indicator of regional development

Transcription

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